AI/ML Engineer II

TENEX.AI is an AI-native, automation-first Managed Detection and Response provider focused on enhancing cybersecurity through advanced solutions. The AI/ML Engineer II will be responsible for designing, developing, and optimizing scalable AI systems, collaborating with engineering teams to implement AI-driven cybersecurity solutions.

Responsibilities:

• Project Execution: Ability to drive and deliver technical components of complex projects. This means communicating effectively to align on requirements, executing on high-quality code, and collaborating with senior engineers and stakeholders throughout the development lifecycle
• AI Layer Engineering: Design & build the AI layer that powers autonomous detection, RAG-backed investigation, and auto-remediation workflows
• Productionize Reasoning Engines: Develop and productionize large-scale LLMs, graph-based reasoning engines, and streaming feature pipelines that operate on billions of security events
• Evaluation & Reliability: Own evaluation & reliability—from prompt libraries and fine-tuning to red-team testing, latency budgets, and fallback strategies
• Cross-Functional Collaboration: Partner tightly with Product, Detection Engineering, and Customer Success to translate real-world attacker behavior into robust ML and rule-based detections
• Push the Frontier: Experiment with retrieval-augmented generation, tool-calling agents, and multi-modal models (text + logs + graphs) to keep defenders decisively ahead

Requirements:

• 3-5 years of experience in software development, engineering production systems using modern programming languages (Python, Go, Rust, or Java)
• Deep knowledge of agentic systems design, such as Centralized and/or Decentralized MAS (Multi-Agent Systems) architectures
• Solid understanding of Graph structures and specifically graph databases
• Hands-on experience building agents, orchestration frameworks (LangChain/LangGraph, Agno AGI, or custom), and evaluation harnesses
• Deep understanding of microservices architecture, containerization (Docker, Kubernetes), and event-driven systems
• Strong fundamentals in API design (REST/gRPC) and distributed systems
• Clear, concise communication skills and a bias for collaborative problem-solving
• Proven track record of gathering consensus and guiding multi-stakeholder initiatives through uncertain boundaries
• Strong problem-solving and analytical skills
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• Prior work in cybersecurity (SIEM, EDR, SOAR, or MDR)
• Background driving high-impact engineering initiatives in high-growth startups or enterprise SaaS
• Familiarity with cloud infrastructure security (AWS, GCP, or Azure)
• Relevant certifications (AWS/GCP Professional Engineer, Kubernetes, or security-related credentials) are a plus